Artificial intelligence in the finance industry


What is artificial intelligence?

Artificial intelligence (AI) technologies are increasingly essential to the world we live in and will need to be deployed at scale in many businesses in order for them to remain relevant. This will require a holistic transformation spanning over multiple layers within the organizations in order to create real value and success.

AI cannot be defined in a consensual way, as every definition has its slight or even broad variation due to the “AI effect,” which with every major breakthrough pushes the AI target and the expectation for real intelligence forward again. It is agreeable that it includes various capabilities, such as (autonomous) machine learning, facial recognition, neuronal networks, computer vision, smart robotics, virtual agents, adaptive predictive power, and autonomous vehicles. But in general it could be defined as the ability of a machine to perform cognitive functions associated with human minds, like e.g. perceiving, reasoning, learning, and problem solving.

Financial institutions, especially banks have always adopted the latest technology innovations to redefine how customers interact with them. In the 1950s and '60s for example they introduced the first ATMs and electronic, card-based payments. In the 1970s the international SWIFT payment network was established and Banks started to invest in computer technology to automate manual processing. In the 1980s, with digital technology well underway, online banking gained popularity and with it came the benefits of lower transaction costs, easier integration of services, and more targeted marketing capabilities. In the 1990s, consumers were introduced to PayPal, a p2p money service enabling wireless transfers. The 2000s saw broad adoption of 24/7 online banking and electronic check clearing and, with the advent of wireless technology and the wide adoption of mobile phones, brought the next major shift in the financial industry called "mobile banking". Fueled by the introduction of smartphones, this made it even more possible for people to manage their financial lives from virtually anywhere and at any time. This was followed not only by the spread of mobile-based “banking on the go” in the 2010s, like Google Wallet and Apple Pay, but also by respective apps, contactless payment via NFC-enabled credit cards and mobile devices, or fingerprint authentication and Touch ID as well as EMV chip technology.

What are its benefits and possibilities?

As the technological progress continues unstoppable, we’re now entering the AI-powered digital age, facilitated by falling costs for data storage and processing, increasing access and connectivity for all, and rapid advances in technologies that lead to higher automation and improved decision making in terms of both speed and accuracy.

A great example for the progress in AI technology was AlphaGo, created by Google DeepMind, as in 2016 it defeated 18-time world champion Lee Sedol at the game of Go, a complex board game requiring intuition, imagination, and strategic thinking—abilities which, until then, have long been considered distinctly human. Since this day, AI technologies have advanced even further and their transformative impact is increasingly evident across industries. AI-powered machines, for example, are tailoring recommendations of digital content to individual tastes and preferences, designing new and advanced forms of clothing, building structures, machines or vehicle bodies, and are even beginning to surpass experienced human capabilities in medical, engineering, bioscience and many other tasks. In 2020, Google DeepMind published Agent57, an AI Agent that widely surpasses human level performance on all 57 games of the Atari2600 suite.

Quantum computing, as one of the next big steps in this technological evolution, will much likely even boost AI capabilities to currently unimaginable levels.

AI technologies cannot only help boost revenues through increased personalization of services to customers and employees. They can also lower costs through efficiencies generated by higher automation, reduced error rates, and better resource utilization, and they can uncover new and previously unrealized opportunities based on an improved ability to process and generate insights from vast amounts of data.

What are the challenges for the finance industry?

However, even though the AI potential for value creation is one of the largest across the finance industry (recent market participant studies from 2020 assume $1 trillion of incremental value for banks, annually) as customer expectations to adoption of digital banking increase, financial institutions struggle to move from experimenting around selected use cases to introducing such technologies across their organizations.

Possible reasons include the lack of a clear strategy and prioritization for AI, an unclear understanding of actual use cases within an organization or pan-organizational, an inflexible or legacy technology core, inadequate investments in AI technologies and talent, fragmented data assets, and outdated operating models impeding collaboration between relevant teams. Moreover, several trends in digital engagement have accelerated during the COVID-19 pandemic and big-tech companies are looking more than ever to enter and disrupt the financial services market.

Despite billions of dollars spent on change-the-bank technology initiatives each year, and even though financial institutions’ use of advanced AI technologies is steadily increasing, in order to successfully compete in this fast changing market, they not only need to achieve the speed, agility, and flexibility of a Fintech. They must also improve managing the scale, security standards, and regulatory requirements of a traditional financial-services enterprise via use of AI.

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